{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# VENN DIAGRAM(维恩图)  \n",
    "维恩图用于显示所有不同组的有限集合之间的可能的逻辑关系。每一组用一个圆圈表示，圆圈大小代表该组的重要性。组通常是重叠的：重叠的大小表示两个组之间的交集。建议不要使Venn图超过3分组，因为它将变得难以阅读。在python中，根据您拥有的组数，使用matplotlib库的venn2和venn3函数来实现Venn图。该章节主要内容有：\n",
    "1. 具有2个分组的基本的维恩图 Venn diagram with 2 groups\n",
    "2. 具有3个组的基本维恩图 Venn diagram with 3 groups\n",
    "3. 自定义维恩图 Custom Venn diagram\n",
    "4. 精致的维恩图 Elaborated Venn diagram\n",
    "5. 维恩图背景色自定义 change background colour of Venn diagram\n",
    "\n",
    "需要安装matplotlib_venn模块：\n",
    "> pip install matplotlib_venn\n",
    "\n",
    "官方文档：\n",
    "https://pypi.org/project/matplotlib-venn/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.core.interactiveshell import InteractiveShell\n",
    "InteractiveShell.ast_node_interactivity = \"all\" "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. 具有2个分组的基本的维恩图 Venn diagram with 2 groups\n",
    "使用matplotlib库制作维恩图的主要方法有2种，但结果相同。第一个步骤是直接给出组及其交叉点的大小。第二个是给定两组值，python将自己计算每组的长度和公共值的数量（它们的交集）。通过venn2计算两个分组。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# library\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib_venn import venn2\n",
    "\n",
    "# 第一种方法，10，5为两组的大小，2为两组交叉大小;\n",
    "# set_labels为组名\n",
    "venn2(subsets = (10, 5, 2), set_labels = ('Group A', 'Group B'));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 设置两组ABCD和DEF\n",
    "venn2([set(['A', 'B', 'C', 'D']), set(['D', 'E', 'F'])]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. 具有3个组的基本维恩图 Venn diagram with 3 groups\n",
    "通过venn3计算3个分组"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Import the library\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib_venn import venn3\n",
    " \n",
    "# Make the diagram\n",
    "venn3(subsets = (10, 8, 22, 6,9,4,2));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 设置三组ABCD、DEF、ADG\n",
    "venn3([set(['A', 'B', 'C', 'D']), set(['D', 'E', 'F']), set(['A', 'D', 'G','F'])]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. 自定义维恩图 Custom Venn diagram  \n",
    "+ Venn上的自定义标签 Custom label on Venn\n",
    "+ 自定义维恩图上圆的线条 Custom Circles lines on Venn\n",
    "+ 自定义维恩图上的圆 Custom a circle on Venn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Venn上的自定义标签 Custom label on Venn\n",
    "# Import the library\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib_venn import venn3\n",
    "from matplotlib_venn import venn3_circles\n",
    "\n",
    "\n",
    "# Custom text labels: change the label of group A\n",
    "v=venn3(subsets = (10, 8, 22, 6,9,4,2), set_labels = ('Group A', 'Group B', 'Group C'))\n",
    "# 单独改变A的标签\n",
    "v.get_label_by_id('A').set_text('My Favourite group!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## 自定义维恩图上圆的线条 Custom Circles lines on Venn\n",
    "# Line style: can be 'dashed' or 'dotted' for example\n",
    "# 设置维恩图\n",
    "v = venn3(subsets = (10, 8, 22, 6,9,4,2), set_labels = ('Group A', 'Group B', 'Group C'))\n",
    "# 画圆，linestyle线条类型，linewith线宽，color线条颜色\n",
    "c = venn3_circles(subsets = (10, 8, 22, 6,9,4,2), linestyle='dashed', linewidth=1, color=\"grey\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## 自定义维恩图上的圆 Custom a circle on Venn\n",
    "# Change one group only\n",
    "v=venn3(subsets = (10, 8, 22, 6,9,4,2), set_labels = ('Group A', 'Group B', 'Group C'))\n",
    "c=venn3_circles(subsets = (10, 8, 22, 6,9,4,2), linestyle='dashed', linewidth=1, color=\"grey\")\n",
    "# 设置第一个圆的线宽\n",
    "c[0].set_lw(8.0)\n",
    "# 设置第一个圆的线形\n",
    "c[0].set_ls('dotted')\n",
    "# 设置第一个圆的填充颜色\n",
    "c[0].set_color('skyblue')\n",
    " \n",
    "# Color\n",
    "# id号\n",
    "# 如ABC三个簇，010代表非A和B和非C,100代表A和非B和非C\n",
    "# 设置透明度\n",
    "v.get_patch_by_id('011').set_alpha(1.0)\n",
    "# 设置颜色\n",
    "v.get_patch_by_id('011').set_color('red')\n",
    "# 打印id号\n",
    "#v.id2idx"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. 精致的维恩图 Elaborated Venn diagram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# libraries\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "from matplotlib_venn import venn3, venn3_circles\n",
    " \n",
    "# Make a Basic Venn\n",
    "# 画最基础维恩图\n",
    "v = venn3(subsets=(1, 1, 1, 1, 1, 1, 1), set_labels = ('A', 'B', 'C'))\n",
    " \n",
    "# Custom it\n",
    "# 设置A和非B和非C颜色为白色,标签为透明\n",
    "v.get_patch_by_id('100').set_alpha(1.0)\n",
    "v.get_patch_by_id('100').set_color('white')\n",
    "v.get_label_by_id('100').set_text('Unknown')\n",
    "# 设置A的标签为'Set \"A\"\n",
    "v.get_label_by_id('A').set_text('Set \"A\"')\n",
    "\n",
    "# 设置圆的线形\n",
    "c = venn3_circles(subsets=(1, 1, 1, 1, 1, 1, 1), linestyle='dashed')\n",
    "# 设置A的线宽和线形\n",
    "c[0].set_lw(1.0)\n",
    "c[0].set_ls('dotted')\n",
    " \n",
    "# Add title and annotation\n",
    "# 添加标签\n",
    "plt.title(\"Sample Venn diagram\")\n",
    "plt.annotate('Unknown set', xy=v.get_label_by_id('100').get_position() - np.array([0, 0.05]), xytext=(-70,-70),\n",
    "ha='center', textcoords='offset points', bbox=dict(boxstyle='round,pad=0.5', fc='gray', alpha=0.1),\n",
    "arrowprops=dict(arrowstyle='->', connectionstyle='arc3,rad=0.5',color='gray'));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. 维恩图背景色自定义 change background colour of Venn diagram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Library\n",
    "from matplotlib import pyplot as plt\n",
    "from matplotlib_venn import venn2\n",
    " \n",
    "# Basic Venn\n",
    "v = venn2( (10, 20, 10), alpha = 1 )\n",
    " \n",
    "# Change Backgroud\n",
    "plt.gca().set_facecolor('skyblue')\n",
    "# 显示边框\n",
    "plt.gca().set_axis_on()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
